Difference between revisions of "Group14 Project Overview"

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==<div id="mw-content-text" lang="en-GB" dir="ltr" class="mw-content-ltr"><div style="background: #6FB1D0; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #6A8295 solid 15px; font-size: 20px; font-family:DIN Alternate"><font color="white">Project Motivation & Problem Statement</font></div>==
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In this age of information, we see an increase in necessity for people and businesses to have a greater access to space and resources to further their personal and corporate needs. Libraries in Singapore are no exception to this trend. 
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In order to meet this necessity, NLB may not only have to find ideal locations within districts for additional libraries, but it also has to manage their resources wisely to meet public demand with respect to each location. Currently there exists this difficulty in measuring the operational readiness of the libraries given that the measure of public demand is not in dollars and cents; unlike that of typical corporations and organizations.
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Constant change management in the location and resources within the libraries have led to the dire need of a reliable and standardized method which can measure the effectiveness of past policies, as well as an accurate predictive model to conduct what-if analyses for future plans. Thus, a user-friendly system which displays geospatial information based on significant data evidence would provide operational insights valuable to the NLB.
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Besides taking geospatial information into consideration, NLB is also motivated to leverage on an effective model (which uses relevant metrics regarding book collections and user transaction information) to accurately measure the attractiveness of existing and potential libraries.
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==<div id="mw-content-text" lang="en-GB" dir="ltr" class="mw-content-ltr"><div style="background: #6FB1D0; padding: 10px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #6A8295 solid 10px; font-size: 20px; font-family:DIN Alternate"><font color="white">Project Objective</font></div>==
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Develop a geospatial dashboard that would facilitate the NLB’s evaluation of different potential library siting locations through better prediction of the catchment and number of patrons it can potentially attract.
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Assess earlier models which have been used to evaluate the attractiveness of libraries and refine them in order to increase the accuracy and reliability of results. 
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Revision as of 22:27, 14 January 2017

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PROJECT OVERVIEW

 

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Project Motivation & Problem Statement

In this age of information, we see an increase in necessity for people and businesses to have a greater access to space and resources to further their personal and corporate needs. Libraries in Singapore are no exception to this trend.

In order to meet this necessity, NLB may not only have to find ideal locations within districts for additional libraries, but it also has to manage their resources wisely to meet public demand with respect to each location. Currently there exists this difficulty in measuring the operational readiness of the libraries given that the measure of public demand is not in dollars and cents; unlike that of typical corporations and organizations.

Constant change management in the location and resources within the libraries have led to the dire need of a reliable and standardized method which can measure the effectiveness of past policies, as well as an accurate predictive model to conduct what-if analyses for future plans. Thus, a user-friendly system which displays geospatial information based on significant data evidence would provide operational insights valuable to the NLB.

Besides taking geospatial information into consideration, NLB is also motivated to leverage on an effective model (which uses relevant metrics regarding book collections and user transaction information) to accurately measure the attractiveness of existing and potential libraries.

Project Objective

Develop a geospatial dashboard that would facilitate the NLB’s evaluation of different potential library siting locations through better prediction of the catchment and number of patrons it can potentially attract.

Assess earlier models which have been used to evaluate the attractiveness of libraries and refine them in order to increase the accuracy and reliability of results.